2019
DOI: 10.1101/819334
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Application of the Hierarchical Bootstrap to Multi-Level Data in Neuroscience

Abstract: A common feature in several types of neuroscience datasets is the presence of hierarchical data structures, such as recording the activity of multiple neurons in multiple animals across multiple trials. Accordingly, the measurements constituting the dataset are not independent, even though the traditional statistical analyses often applied in such cases (e.g. Student's t-test) treat them as such. The hierarchical bootstrap has been shown to be an effective tool to accurately analyze such data and while it has … Show more

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Cited by 123 publications
(146 citation statements)
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“…Here, all trial epochs of 5-15 cm/s movement were concatenated by subject before calculating PSD or coherence, capturing all spectral data for that subject. For theta band power correlations and theta phase lags, comparisons between the sexes and between estrous stages were analyzed using a hierarchical bootstrapping approach adapted from Saravanan et al (29). Trials were bootstrapped to subject, resampling data 10 4 permutations with replacement.…”
Section: Estrous Stage Determinationmentioning
confidence: 99%
See 1 more Smart Citation
“…Here, all trial epochs of 5-15 cm/s movement were concatenated by subject before calculating PSD or coherence, capturing all spectral data for that subject. For theta band power correlations and theta phase lags, comparisons between the sexes and between estrous stages were analyzed using a hierarchical bootstrapping approach adapted from Saravanan et al (29). Trials were bootstrapped to subject, resampling data 10 4 permutations with replacement.…”
Section: Estrous Stage Determinationmentioning
confidence: 99%
“…Correlation coefficients were then analyzed as a function of biological sex and as a function of the female estrous stage using a hierarchical bootstrapping method of data resampling (29).…”
mentioning
confidence: 99%
“…In this experiment, one of the seven TRPV1-Cre::ChR2 mice was removed from the data set because it displayed saturating responses to Protocol 3 preventing comparison of values across a dynamic range. Response latencies, response rise times and response durations were computed using a hierarchical bootstrap procedure (Saravanan et al, 2019) modified to acquire bootstrap estimates of the median with balanced resampling. Briefly, mice are sampled with replacement for the number of times that there are mice.…”
Section: Discussionmentioning
confidence: 99%
“…All statistical tests were performed with custom code in MATLAB. For fly walking behavior in Figure 7, we used bootstrap simulations with 10,000 random draws to compare both the likelihood of stationary flies to start walking, as well as changes in walking speed (Saravanan et al, 2019). Stationary trials were assigned a binary value to indicate that the fly began walking (1) or not (0).…”
Section: Statistical Analysesmentioning
confidence: 99%